A majorization-minimization based solution to penalized nonnegative matrix factorization with orthogonal regularization
DOI10.1016/j.cam.2022.114877OpenAlexW4303520812MaRDI QIDQ2095174
Can Tong, Jiao Wei, Yueyang Teng, Tie Zhang, Shouliang Qi, Yu-Dong Yao
Publication date: 9 November 2022
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cam.2022.114877
Kullback-Leibler divergencenonnegative matrix factorizationmajorization-minimization methodorthogonal regularization
Computational methods for sparse matrices (65F50) Factorization of matrices (15A23) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Orthogonalization in numerical linear algebra (65F25)
Cites Work
- An alternating direction algorithm for matrix completion with nonnegative factors
- Matching theory
- Two fast vector-wise update algorithms for orthogonal nonnegative matrix factorization with sparsity constraint
- SVD based initialization: A head start for nonnegative matrix factorization
- A convergent algorithm for orthogonal nonnegative matrix factorization
- Low-rank nonnegative matrix factorization on Stiefel manifold
- A convergent non-negative deconvolution algorithm with Tikhonov regularization
- Learning the parts of objects by non-negative matrix factorization
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